Acoustic tracking and localization using computationally efficient algorithms

Abstract

U.S. Army Research Laboratory (ARL) is developing low size, weight, power, and cost (SWAP-C) solutions for acoustic detection, tracking, and localization of moving targets. Many standard signal processing algorithms cannot be implemented on low SWAP-C commercial off-the-shelf (COTS) hardware for unattended ground sensor applications due to power and computational requirements. To overcome this issue, ARL is developing lower complexity beamforming, tracking and localization algorithms. For example, beamformer algorithms are based upon 1-dimensional scans, multi hypothesis target trackers are based on alpha beta filters and localization algorithms are based upon linear least squares algorithms. The performance of these algorithms is slight poorer than other standard approaches, but their computational complexity can be lower by an order of magnitude.U.S. Army Research Laboratory (ARL) is developing low size, weight, power, and cost (SWAP-C) solutions for acoustic detection, tracking, and localization of moving targets. Many standard signal processing algorithms cannot be implemented on low SWAP-C commercial off-the-shelf (COTS) hardware for unattended ground sensor applications due to power and computational requirements. To overcome this issue, ARL is developing lower complexity beamforming, tracking and localization algorithms. For example, beamformer algorithms are based upon 1-dimensional scans, multi hypothesis target trackers are based on alpha beta filters and localization algorithms are based upon linear least squares algorithms. The performance of these algorithms is slight poorer than other standard approaches, but their computational complexity can be lower by an order of magnitude.